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Automatic Classification of Neural Data

By Juan Martínez Gómez


In this thesis we present a new solution for an automatic classification of the single-neuron activity. The study of the computational role of individual neurons underlying different cognitive process is a gold standard in Neuroscience. This type of analysis is done first, by recording the extracellular spikes of the neurons near the tip of a microelectrode and second, by isolating the spikes of the recorded cells based on the similarity of their shapes using a method called spike sorting.\ud In recent years, important advances in microelectrode technology allow us now to perform massive parallel recordings using a high number of channels with the possibility to study the activity of large ensembles of neurons at a time. However, this fascinating opportunity introduces at the same time a challenge for the efficient and fast analysis of this data.\ud In this research work, we address this problem by developing a new implementation for unsupervised spike sorting that improves the performance of a widely-used spike sorting algorithm, increasing the number of automatically identified neurons. Moreover, we developed a new testing platform which generates simulations of extracellular recordings including challenging conditions such as realistic noise, multi-unit activity -spikes of distant neurons impossible to be identified as single units- or the presence of neurons with low firing rates.\ud In summary, the results presented here provide contributions to the development of automated and efficient quantitative frameworks for the analysis of multiple-channel recordings that help us to understand single-neuron population codes

Publisher: University of Leicester
Year: 2011
OAI identifier: oai:lra.le.ac.uk:2381/9696

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  1. (2002). A method for spike sorting and detection based on wavelet packets and shannon’s mutual information. doi
  2. (2008). A nonparametric bayesian alternative to spike sorting. doi
  3. (1998). A review of methods for spike sorting: The detection and classification of neural action potentials. Network: Computation in Neural Systems, doi
  4. (1979). A review of the hippocampal place cells. doi
  5. (1989). A theory for multiresolution signal decomposition: the wavelet representation. doi
  6. (2007). A tool for synthesizing spike trains with realistic interference. doi
  7. (2000). Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements.
  8. (2001). Actions from thoughts.
  9. (1978). Activity of human hippocampal formation and amygdala neurons during memory testing. doi
  10. (2002). An ultra-sparse code underlies the generation of neural sequences in a songbird. doi
  11. (1996). Automatic sorting of multiple unit neuronal signals in the presence of anisotropic and non-gaussian variability. doi
  12. (2004). Automatic spike sorting for neural decoding. doi
  13. (1994). Bayesian modeling and classification of neural signals. doi
  14. (1969). Bioelectry phenomena.
  15. (2002). Brain-machine interface: instant neural control of a movement signal. doi
  16. (2000). Category-specific visual responses of single neurons in the human medial temporal lobe.
  17. (1998). Chronic recording capability of the utah intracortical electrode array in cat sensory cortex. doi
  18. (1998). Classification of non-stationary neural signal. doi
  19. (1997). Coding of intention in the posterior parietal cortex. doi
  20. (2004). Cognitive control signals for neural prosthetics. doi
  21. (2004). Cognitive neural prosthetics. Trends Cogn. doi
  22. (1985). Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex.
  23. (1989). Comparison between cluster monte carlo algorithms in the ising spin model. doi
  24. (1992). Cortical cells should fire regularly, but do not. doi
  25. (1997). Data clustering using a model granular magnet. doi
  26. (1997). Detection, classification, and superposition resolution of action potentials in multi-unit single-channel recordings by an on-line real-time neural network. doi
  27. (2002). Dynamical properties of constrained drops. doi
  28. (1993). Dynamics of the hippocampal ensemble code for space. doi
  29. (1901). E´tude comparative de la distribution florale dans une portion des alpes et des jura.
  30. (1999). Electrical interactions via extracellular potential near cell bodies.
  31. (1962). Electrophysiology of a dendritic neuron model. doi
  32. (2008). Encoding of naturalistic stimuli by local field potential spectra in networks of excitatory and inhibitory neurons. doi
  33. (2009). Extracting information from neuronal populations: information theory and decoding approaches. doi
  34. (1909). Histologie du systeme nerveux de l’homme et des vertebres. doi
  35. (2006). How silent is the brain: Is there a dark matter problem in neuroscience? doi
  36. (2008). Human single-neuron responses at the threshold of conscious recognition. doi
  37. (1994). Ideal spatial adaptation by wavelet shrinkage. doi
  38. (1996). Inferotemporal cortex and object vision. doi
  39. (2004). Intersection of microwire electrodes with proximal ca1 stratum-pyramidale neurons at insertion for multiunit recordings predicted by a 3-d computer model. doi
  40. (2007). Interspike interval distributions, spike sorting, and real experimental conditions. The British Neuroscience Association Meeting,
  41. (2000). Intracellular features predicted by extracellular recordings in the hippocampus in vivo.
  42. Invariant visual representation by single-neurons in the human brain. doi
  43. (2004). Large-scale recording of neuronal ensembles. doi
  44. (1993). Magnetoencephalography -theory, instrumentation, and applications to noninvasive studies of working human brain. doi
  45. (2003). Massively parallel recording of unit and local field potentials with silicon-based electrodes. doi
  46. (2006). Model of low-pass filtering of local field potentials in brain tissue. doi
  47. (2003). Model-based 3d cortical neuron localization and classification with silicon electrode arrays. Soc Neurosci Abstr.
  48. (1988). Monte carlo simulations in statistical physics: An introduction. doi
  49. (2006). Movement intention is better predicted than attention in the posterior parietal cortex. doi
  50. (2002). Multielectrode recordings: the next steps. Current Opinion in Neurobiology, doi
  51. (1996). Nature and precision of temporal coding in visual cortex: a metric-space analysis.
  52. (2006). Neural correlations, population coding and computation. doi
  53. (1986). Neuronal population coding on movement direction. doi
  54. (1994). Nmdareceptor channel diversity in the developing cerebellum. doi
  55. (2006). On the origin of the extracellular action potential waveform: a modeling study. doi
  56. (2004). On the variability of manual spike sorting. doi
  57. (2002). Oscillations and sparsening of odor representations in the mushroom body. doi
  58. (1990). Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn Reson Med, doi
  59. (1988). Performance of planar multisite microprobes in recording extracellular single-unit intracortical activity. doi
  60. (1993). Phase relationship between hippocampal place units and the eeg theta rythm. doi
  61. (2002). Place cells and place recognition maintained by direct entorhinal-hippocampal circuitry. doi
  62. (1976). Place units in the hippocampus of the freely moving rat. doi
  63. (2007). Predicting movement from multiunit activity. doi
  64. (2009). Realistic simulation of extracellular recordings. doi
  65. (1962). Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. doi
  66. (2006). Rhythms of the brain. doi
  67. (2003). Robust, automatic spike sorting using mixtures of multivariate t-distributions. doi
  68. (1993). Selectivity for polar, hyperbolic, and cartesian gratings in macaque visual cortex. doi
  69. (1994). Shape representation in the inferior temporal cortex of monkeys. doi
  70. (1994). Silicon ribbon cables for chronically implantable microelectrode arrays. doi
  71. (1999). Simulataneous paired intracellular and tetrode recordings for evaluating the performance of spike sorting algorithms. doi
  72. (1964). Simultaneous studies of firing patterns in several neurons. doi
  73. (1997). Single neuron activity in human hippocampus and amygdala during recognition of faces and objects. doi
  74. (2000). Spike sorting based on discrete wavelet transform coefficients. doi
  75. (2006). Spike sorting: Bayesian clustering of non-stationary data. doi
  76. (2005). Spike source localization with tetrodes. doi
  77. (1997). Spikes: Exploring the neural code. doi
  78. (1984). Stimulus-selective properties of inferior temporal neurons in the macaque. doi
  79. (1999). Super-paramagnetic clustering of data: the definitive solution of an ill-posed problem. doi
  80. (1996). Super-paramagnetic clustering of data. doi
  81. (1987). Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. iii. information theoretic analysis.
  82. (1995). Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex. doi
  83. (1928). The basis of sentations.
  84. (1968). The electrical properties of metal microelectrodes. doi
  85. (1988). The intrinsic electrophysiological properties of mammalian neurons: insights into central nervous system function. doi
  86. (1997). The neuron simulation environment. doi
  87. (1982). The potts model. doi
  88. (1983). The stereotrode: a new technique for simultaneous isolation of several single units in the central nervous system from multiple unit records. doi
  89. (1998). The variable discharge of cortical neurons: Implications for connectivity, computation, and information coding.
  90. (1957). Tungsten microelectrodes for recording single units. doi
  91. (1990). Two-photon laser scanning fluorescence microscopy. doi
  92. (2004). Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. doi
  93. (2002). Using noise signature to optimize spike-sorting and to assess neuronal classification quality. doi
  94. (1996). Variability of extracellular spike waveforms of cortical neurons.
  95. (1972). Visual properties of neurons in inferotemporal cortex of the macaque.
  96. (1969). Visual receptive fields of neurons in inferotemporal cortex of the monkey. doi
  97. (2004). Vsdi: A new era in functional imaging of cortical dynamics. doi
  98. (2008). What can we do and what cannot do with fmri. doi
  99. (2003). What determines the frequency of fast network oscillations with irregular neural discharges? doi
  100. (2009). What is the real shape of extracellular spikes? doi

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